78 citations · 87 across the 5 of their papers we have counts for
5 papers
Context-aware Domain Adaptation for Time Series Anomaly Detection
Kwei-Herng Lai, Lan Wang, Huiyuan Chen +4
Time series anomaly detection is a challenging task with a wide range of real-world applications. Due to label sparsity, training a deep anomaly detector often relies on unsupervis…
Denoising Self-attentive Sequential Recommendation
Huiyuan Chen, Yusan Lin, Menghai Pan +6
Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies. This is mainly attributed to their unique self…
SMARTQUERY: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction
Xiaoting Li, Yuhang Wu, Vineeth Rakesh +3
Graph neural networks have achieved significant success in representation learning. However, the performance gains come at a cost; acquiring comprehensive labeled data for training…
Forecast-based Multi-aspect Framework for Multivariate Time-series Anomaly Detection
Lan Wang, Yusan Lin, Yuhang Wu +3
Today's cyber-world is vastly multivariate. Metrics collected at extreme varieties demand multivariate algorithms to properly detect anomalies. However, forecast-based algorithms,…
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection
Yuhang Wu, Mengting Gu, Lan Wang +3
Modeling inter-dependencies between time-series is the key to achieve high performance in anomaly detection for multivariate time-series data. The de-facto solution to model the de…